Interference estimation and adaptive reconfiguration of a capacitive touch controller

ABSTRACT

Adaptive reconfiguration of a capacitive touch controller is implemented by estimating the interference spectrum of the signal received by the touch controller. The spectrum of the received signal is used to determine a desired frequency, and the touch panel transmitter is configured to use that desired frequency. The spectrum of the received signal is also used to determine an desired filter transfer function. A filter in the touch panel received signal path is configured to use that desired filter transfer function. The adaptive reconfiguration is focused on improving the signal to noise ratio of the received signal without the need for shielding the touch panel, performing additional scans of the touch panel, or using components that operate at higher power levels.

CROSS REFERENCE TO RELATED APPLICATION

The present application claims the benefit of the filing date under 35U.S.C. §119(e) of Provisional U.S. Patent Application Ser. No.61/584,477, which was filed on Jan. 9, 2012, and is hereby incorporatedherein by reference in its entirety.

TECHNICAL FIELD

This disclosure relates to methods and apparatus for capacitive touchscreen devices.

BACKGROUND

Continual development and rapid improvement in portable devices hasincluded the incorporation of touch screens in these devices. A touchscreen device responds to a user's touch to convey information aboutthat touch to a control circuit of the portable device. The touch screenis conventionally combined with a generally coextensive display devicesuch as a liquid crystal display (LCD) to form a user interface for theportable device. The touch screen also operates with a touch controllercircuit to form a touch screen device. In other applications using touchsensing, touch pads may also be part of the user interface for a devicesuch as a personal computer, taking the place of a separate mouse foruser interaction with the onscreen image. Relative to portable devicesthat include a keypad, rollerball, joystick or mouse, the touch screendevice provides advantages of reduced moving parts, durability,resistance to contaminants, simplified user interaction and increaseduser interface flexibility.

Despite these advantages, conventional touch screen devices have beenlimited in their usage to date. For some devices, current drain has beentoo great. Current drain directly affects power dissipation which is akey operating parameter in a portable device. For other devices,performance such as response time has been poor, especially whensubjected to fast motion at the surface of the touch screen. Somedevices do not operate well in environments with extreme conditions forelectromagnetic interference and contaminants that can affectperformance.

Further limitations and disadvantages of conventional and traditionalapproaches will become apparent to one of ordinary skill in the artthrough comparison of such approaches with aspects of the presentdisclosure as set forth in the remainder of this application and withreference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The system may be better understood with reference to the followingdrawings and description. In the figures, like reference numeralsdesignate corresponding parts throughout the different views.

FIG. 1 is a block diagram of an exemplary portable device.

FIG. 2 includes FIG. 2A which shows a top view of a portable device andFIG. 2B which shows a cross-sectional view of the portable device alongthe line B-B′.

FIG. 3 is a simplified diagram of an exemplary mutual capacitance touchpanel for use in the portable device of FIGS. 1 and 2.

FIG. 4 shows an exemplary block diagram of the touch front end of theportable device of FIG. 1.

FIG. 5 shows an exemplary first sample asymmetric scan map.

FIG. 6 shows an exemplary second sample asymmetric scan map.

FIG. 7 shows an exemplary high-level architecture of the touch front endof the portable device of FIG. 1.

FIG. 8 shows a simplified capacitive touch panel and related circuitry;

FIG. 9 illustrates an exemplary baseline tracking filter for use in acontroller circuit for a portable device.

FIG. 10 shows an exemplary first variance estimator in conjunction withthe baseline tracking filter of FIG. 9.

FIG. 11 shows an exemplary second variance estimator in conjunction withthe baseline tracking filter of FIG. 9.

FIG. 12 shows an exemplary flow-chart for the adaptive reconfigurationof a capacitive touch controller.

FIG. 13 shows an exemplary differential scan data path with decimation,interference, and integration filters, using an in-phase (I) path and aquadrature (Q) path.

FIG. 14A shows an implementation of a single ended scan data path withdecimation, interference, and integration filters.

FIG. 14B shows an implementation of a single ended scan data path withdecimation, interference, and integration filters, where the integrationfilter is an infinite impulse response (IIR) filter cascaded with afinite impulse response (FIR) filter.

FIG. 14C shows an implementation of an exemplary single ended scan datapath with decimation, interference, and integration filters, where theintegration filter is an infinite impulse response (IIR) filter cascadedwith a finite impulse response (FIR) filter.

FIG. 15 shows a diagram of the details of exemplary portions of theadaptive reconfiguration, where the scan data path block includesdecimation filters, integration filters (bandpass integrators),differentiation filters (bandpass differentiator), interferer filters,and differential in-phase (I) and quadrature (Q) outputs.

FIG. 16 shows exemplary graphs of the interference profile of thereceived signal when the touch panel device is operating in twodifferent modes.

FIG. 17 shows an exemplary graph of the spectral components of thereceived signal including the interference profile of the receivedsignal and the desired signal.

FIG. 18 shows exemplary graphs of the spectral components of thereceived signal before and after filtering with a filter transferfunction.

DETAILED DESCRIPTION

Referring now to FIGS. 1 and 2, FIG. 1 shows a block diagram of aportable device 100. FIG. 2 is one embodiment of a portable device 100according to the block diagram of FIG. 1. As shown in FIG. 1, theportable device 100 includes a capacitive touch panel 102, a controllercircuit 104, a host processor 106, input-output circuit 108, memory 110,a liquid crystal display (LCD) 112 and a battery 114 to provideoperating power.

FIG. 2 includes FIG. 2A which shows a top view of the portable device100 and FIG. 2B which shows a cross-sectional view of the portabledevice 200 along the line B-B′. The portable device may be embodied asthe widest variety of devices including as a tablet computer, a smartphone, or even as a fixed device with a touch-sensitive surface ordisplay.

The portable device 100 includes a housing 202, a lens or clear touchsurface 204 and one or more actuatable user interface elements such as acontrol switch 206. Contained within the housing are a printed circuitboard 208 circuit elements 210 arranged on the printed circuit board 208and as are shown in block diagram form in FIG. 1. The capacitive touchpanel 102 is arranged in a stack and includes a drive line 212, aninsulator 214 and a sense line 216. The insulator electrically isolatesthe drive line 212 and other drive lines arranged parallel to the driveline from the sense lines 216. Signals are provided to one or more ofthe drive lines 212 and sensed by the sense lines 216 to locate a touchevent on the clear touch surface 204. The LCD 112 is located between theprinted circuit board 208 and the capacitive touch panel 102.

As particularly shown in FIG. 2A, the capacitive touch panel 102 and theLCD 112 may be generally coextensive and form a user interface for theportable device. Text and images may be displayed on the LCD for viewingand interaction by a user. The user may touch the capacitive touch panel102 to control operation of the portable device 100. The touch may be bya single finger of the user or by several fingers, or by other portionsof the user's hand or other body parts. The touch may also be by astylus gripped by the user or otherwise brought into contact with thecapacitive touch panel. Touches may be intentional or inadvertent. Inanother application, the capacitive touch panel 102 may be embodied as atouch pad of a computing device. In such an application, the LCD 112need not be coextensive (or co-located) with the capacitive touch panel102 but may be located nearby for viewing by a user who touches thecapacitive touch panel 102 to control the computing device.

Referring again to FIG. 1, the controller circuit 104 includes a digitaltouch system 120, a processor 122, memory including persistent memory124 and read-write memory 126, a test circuit 128 and a timing circuit130. In one embodiment, the controller circuit 104 is implemented as asingle integrated circuit including digital logic and memory and analogfunctions.

The digital touch subsystem 120 includes a touch front end (TFE) 132 anda touch back end (TBE) 134. This partition is not fixed or rigid, butmay vary according to the high-level function(s) that each blockperforms and that are assigned or considered front end or back endfunctions. The TFE 132 operates to detect the capacitance of thecapacitive sensor that comprises the capacitive touch-panel 102 and todeliver a high signal to noise ratio (SNR) capacitive image (or heatmap)to the TBE 134. The TBE 134 takes this capacitive heatmap from the TFE132 and discriminates, classifies, locates, and tracks the object(s)touching the capacitive touch panel 102 and reports this informationback to the host processor 106. The TFE 132 and the TBE 134 may bepartitioned among hardware and software or firmware components asdesired, e.g., according to any particular design requirements. In oneembodiment, the TFE 132 will be largely implemented in hardwarecomponents and some or all of the functionality of the TBE 134 may beimplemented by the processor 122.

The processor 122 operates in response to data and instructions storedin memory to control the operation of the controller circuit 104. In oneembodiment, the processor 122 is a reduced instruction set computer(RISC) architecture, for example as implemented in an ARM processoravailable from ARM Holdings. The processor 122 receives data from andprovides data to other components of the controller circuit 104. Theprocessor 122 operates in response to data and instructions stored inthe persistent memory 124 and read-write memory 126 and in operationwrites data to the memories 124, 126. In particular, the persistentmemory 124 may store firmware data and instructions which are used byany of the functional blocks of the controller circuit 104. These dataand instructions may be programmed at the time of manufacture of thecontroller 104 for subsequent use, or may be updated or programmed aftermanufacture.

The timing circuit 130 produces clock signals and analog, time-varyingsignals for use by other components of the controller circuit 104. Theclock signals include digital clock signals for synchronizing digitalcomponents such as the processor 122. The time-varying signals includesignals of predetermined frequency and amplitude for driving thecapacitive touch panel 102. In this regard, the timing circuit 130 mayoperate under control or responsive to other functional blocks such asthe processor 122 or the persistent memory 124.

FIG. 3 shows a diagram of a typical mutual capacitance touch panel 300.The capacitive touch panel 300 models the capacitive touch panel 102 ofthe portable device of FIGS. 1 and 2. The capacitive touch panel 300 hasN_(row) rows and N_(col) columns (N_(row)=4, N_(col)=5 in FIG. 3). Inthis manner, the capacitive touch panel 300 creates N_(row)×N_(col)mutual capacitors between the N_(row) rows and the N_(col) columns.These are the mutual capacitances that the controller circuit 104commonly uses to sense touch, as they create a natural grid ofcapacitive nodes that the controller circuit 104 uses to create thetypical capacitive heatmap. However, it is worth noting that there are atotal of (N_(row)+N_(col))—or (N_(row)N_(col)+2) nodes if a touchingfinger or stylus and ground node in the capacitive touch panel 300 areincluded. A capacitance exists between every pair of nodes in thecapacitive touch panel 300.

Stimulus Modes

The capacitive touch panel 300 can be stimulated in several differentmanners. The way in which the capacitive touch panel 300 is stimulatedimpacts which of the mutual capacitances within the panel are measured.A list of the modes of operation is detailed below. Note that the modesdefined below only describe the manner in which the TFE 132 stimulatesthe panel.

Row-column (RC) mode is a first operating mode of a mutual capacitivesensor. In RC mode, the rows are driven with transmit (TX) waveforms andthe columns are connected to receive (RX) channels of the TFE 132.Therefore, the mutual capacitors between the rows and the columns aredetected, yielding the standard N_(row)×N_(col) capacitive heatmap. Inthe example shown in FIG. 3, RC mode measures the capacitors labeledC_(r<i>,c<j>), where <i> and <j> are integer indices of the row andcolumn, respectively. Generally, there is no incremental value insupporting column-row (CR) mode, (e.g. driving the columns and sensingthe rows), as it yields the same results as RC mode.

Self-capacitance column (SC) mode is a self-capacitance mode that may besupported by the controller 102. In SC mode, one or more columns aresimultaneously driven and sensed. As a result, the total capacitance ofall structures connected to the driven column can be detected.

In column-listening (CL) mode, the RX channels are connected to thecolumns of the capacitive touch panel 102 and the transmitter is turnedoff. The rows of the capacitive touch panel 102 will either be shortedto a low-impedance node (e.g. AC ground), or left floating (e.g.high-impedance). This mode is used to listen to the noise andinterference present on the panel columns. The output of the RX channelswill be fed to a spectrum estimation block in order to determine theappropriate transmit signal frequencies to use and the optimalinterference filter configuration, as will be described in furtherdetail below.

Timing Terminology

Some terminology is introduced for understanding the various timescalesby which results are produced within the TFE 132. The TFE 132 produces acapacitive heatmap by scanning all desired nodes of the capacitive touchpanel 102 (e.g., all of the nodes, or some specified or relevant subsetof all of the nodes). This process may be referred to as a frame scan;the frame scan may run at a rate referred to as the frame rate. Theframe rate may be scalable. One exemplary frame rate includes a framerate of 250 Hz for single touch and a panel size less than or equal to5.0 inches in size. A second exemplary frame rate is 200 Hz for singletouch and a panel size greater than 5.0 inches. A third exemplary framerate is 120 Hz minimum for 10 touches and a panel size of 10.1 inches.Preferably, the controller 104 can support all of these frame rates andthe frame rate is configurable to optimize tradeoff of performance andpower consumption for a given application. The term scan rate may beused interchangeably with the term frame rate.

The controller circuit 104 may assemble a complete frame scan by takinga number of step scans. Qualitatively, each step scan may result in aset of capacitive readings from the receivers, though this may not bestrictly done in all instances. The controller circuit 104 may performeach step scan at the same or different step rate. For row/column (RC)scan, where the transmitters are connected to the rows and the receiversare connected to the columns, it will take N_(row) step scans to createa full frame scan. Assuming a tablet-sized capacitive touch panel 102with size 40 rows×30 columns, the step rate may be at least 8 kHz toachieve a 200 Hz frame rate.

For all mutual-capacitance scan modes a touch event causes a reductionin the mutual capacitance measured. The capacitive heatmap that iscreated by the TFE 132 will be directly proportional to the measuredcapacitance. Therefore, a touch event in these scan modes will cause areduction in the capacitive heatmap. For all self-capacitance scanmodes, a touch event causes an increase in the capacitance measured. Thecapacitive heatmap that is created by the TFE 132 will be directlyproportional to the measured capacitance. Therefore, a touch event inthese scan modes will cause a local increase in the capacitive heatmap.

Referring now to FIG. 4, it shows a block diagram of the touch front end(TFE) 132 of FIG. 1. In the illustrated embodiment, the TFE 132 includes48 physical transmit channels and 32 physical receive channels.Additionally, some embodiments of the TFE 132 may contain circuitry suchas power regulation circuits, bias generation circuits, and clockgeneration circuitry. To avoid unduly crowding the drawing figure, suchmiscellaneous circuitry is not shown in FIG. 4.

The TFE 132 includes transmit channels 402, a waveform generation block404, receive channels 406 and I/Q scan data paths 408. The transmitchannels 402 and the receive channels 406 collectively may be referredto as the analog front end (AFE) 400. The TFE 132 further includes, forthe in-phase results from the I/Q scan data path, a receive datacrossbar multiplexer 410, a differential combiner 412 and an in-phasechannel assembly block 414. Similarly for the quadrature results, theTFE 132 includes a receive data crossbar multiplexer 416, a differentialcombiner 418 and an in-phase channel assembly block 420. The in-phaseresults and the quadrature results are combined in an I/Q combiner 422.The absolute value of the data is provided to a row and columnnormalizer 424 and then made available to the touch back end (TBE) 134.Similarly, the heatmap phase information from the I/Q combiner 422 isprovided to the TBE 134 as well.

The TFE 132 further includes a scan controller 426, read controlcrossbar multiplexer 428 and transmit control crossbar multiplexer 430.Further, the TFE 132 includes a spectrum estimation processor 426 aswill be described below in further detail. The spectrum estimationprocessor 426 provides a spectrum estimate to the TBE 134. The scancontroller 426 receives high level control signals from the TBE 134 tocontrol which columns are provided with transmit signals and which rowsare sensed.

The receive data crossbar multiplexers 410, 416 and the receive controlcrossbar multiplexer 428 together form a receive crossbar multiplexer.These two multiplexers are used to logically remap the physical receiveTFE channels by remapping both their control inputs and data outputs. Assuch, the control signals routed to both multiplexers may be identical,as the remapping performed by the receive data multiplexers 410, 416 andthe receive control multiplexer 428 needs to be identical.

The receive data crossbar multiplexers 410, 416 sit between the outputof the I/Q scan data path 408 and the heatmap assembly blocks 414, 420.The purpose of the receive data crossbar multiplexers 410, 416 is toenable the logical remapping of the receive channels. This in turnallows for logical remapping of the electrical connectors such as pinsor balls which connect the integrated circuit including the controller104 to other circuit components of the portable device 100. This will inturn enable greater flexibility in routing a printed circuit board fromthe integrated circuit including the controller 104 to the capacitivetouch panel 102.

Since the I/Q scan data path 408 outputs complex results, the receivecrossbar multiplexer may be able to route both the I and Q channels ofthe scan data path output. This can easily be achieved by instantiatingtwo separate and identical crossbar multiplexers 410, 416. These twomultiplexers will share the same control inputs.

The receive control crossbar multiplexer 428 sits between the scancontroller 426 and the AFE 400. It is used to remap the per-channelreceive control inputs going into the AFE 400. The structure of thereceive control crossbar multiplexer 428 may be the same as for thereceive data crossbar multiplexers 410, 416.

Since the Rx Ctrl crossbar is used in conjunction with the Rx Datacrossbar to logically remap the RX channels, it may be programmed inconjunction with the Rx data crossbar. The programming of the receivecontrol multiplexer 428 and the receive data crossbar multiplexers 410,416 are not identical. Instead the programming may be configured so thatthe same AFE to controller channel mapping achieved in one multiplexeris implemented in the other.

The scan controller 426 forms the central controller that facilitatesscanning of the capacitive touch panel 102 and processing of the outputdata in order to create the capacitive heatmap. The scan controller 426operates in response to control signals from the TBE 134.

Scan Controller Modes of Operation

The scan controller 426 may support many different modes. A briefdescription of each mode is listed below. Switching between modes istypically performed at the request of the processor 122 (FIG. 1), with afew exceptions noted below.

Active scan mode is considered the standard mode of operation, where thecontroller 104 is actively scanning the capacitive touch panel 102 inorder to measure the capacitive heatmap. Regardless of what form ofpanel scan is utilized, the scan controller 426 steps through a sequenceof step scans in order to complete a single frame scan.

In single-frame mode, the controller initiates one single frame scan atthe request of the processor 122. After the scan is complete, thecapacitive heatmap data is made available to the processor 122 and thescan controller 426 suspends further operation until additionalinstructions are received from the processor 426. This mode isespecially useful in chip debugging.

In single-step mode, the controller initiates one single step scan atthe request of the processor 122. After the scan is complete, theoutputs of the scan data path 408 are made available to the processor122 and the scan controller 426 suspends further operation untiladditional instructions are received from the processor 122. This modeis especially useful in chip testing and debugging.

Idle scan mode is a mode initiated by the processor 122 in order to runthe controller 104 in a lower-performance mode. Typically, this modewill be selected when the controller 122 does not detect an active touchon the screen of the capacitive touch panel 102, but still wantsreasonably fast response to a new touch. Therefore, the controller 122is still active and capable of processing the heatmap data produced bythe TFE 132.

The primary differences between active scan mode and idle scan mode aretwofold. First, the frame rate in idle scan mode will typically beslower than that used in active scan mode. Duty cycling of the AFE 400and other power reduction modes will be used in order to reduce totalpower consumption of the controller 104 during idle scan. Second, thelength of time used to generate a single frame scan may be shorter inidle scan mode than in active scan mode. This may be achieved by eithershortening the duration of a step scan or by performing fewer step scansper frame. Reducing total frame scan time can further reduce power atthe expense of reduced capacitive heatmap signal to noise ratio (SNR).

Spectrum estimation mode is used to measure the interference and noisespectrum coupling into the receive channels. This measurement is thenanalyzed by the processor 122 to determine the appropriate transmitfrequency and calculate the optimal filter coefficients for the filterswithin the scan data path 408. This mode is typically used with theColumn Listening mode.

In spectrum estimation mode, most of the blocks of the TFE 132 in FIG. 4are disabled. The scan controller 426, the AFE 400, and the spectrumestimation preprocessor 432 may be used. The transmit channel 402 of theAFE 400 is powered down, and the receive channel 406 of the AFE 400records the background noise and interference signals that couple intothe capacitive touch panel 102. The receive data from all of thechannels of the AFE 400 are routed to the spectrum estimationpreprocessor 432, which performs mathematical preprocessing on thisdata. The output of the spectrum estimation preprocessor 432 will be anN-point vector of 16-bit results, where N is approximately 200 when thesample rate is approximately 2 MHz. The output of the spectrumestimation preprocessor 432 is handed off to the processor 122 forfurther analysis and determination of the appropriate transmit frequencyto use. This process is described in greater detail below.

In addition to the functional modes described above, the controller 104may have a set of sleep modes, where various functional blocks in thecontroller 104 are disabled and/or powered down completely.

A frame scan includes of a series of step scans. The structure of eachstep scan may be identical from step scan to the next within a givenframe scan; however, the exact values of control data vary from stepscan to step scan. Furthermore, the operation of a given frame scan maybe determined by configuration parameters and may or may not affected bydata values measured by the receive channel. One example of the framescan logic that the controller circuit 104 may implement is shown below.

// Initialization Set DDFS parameters; Clear heatmap_memory; // Stepscan loop For step_idx = 1 to num_step_scans {     // Configure circuitsaccording to step_idx     Set scan_datapath_control to    scan_datapath_parameters[step_idx];     Assert Rx_reset and wait TBDclock cycles;     Set AFE_control_inputs to AFE_parameters[step_idx];    Deassert Rx_reset and wait TBD clock cycles;     // Run step scanand collect data     Send start signal to DDFS and scan data path;    Wait for TBD clock cycles for step scan to complete;     Passdatapath_results[step_idx] to heatmap assembly block     // Incrementalheatmap processing } // step_idx loop

The incremental heatmap processing operation is described in greaterdetail below.

Multi-Transmit Support and Block Stimulation of the Panel

In order to achieve improved SNR in the capacitive heatmap, thecontroller circuit 104 provides support for multi-transmit (multi-Tx)stimulation of the capacitive control panel 102. Multi-Tx stimulation(or Multi-Tx) means that multiple rows of the panel are simultaneouslystimulated with the transmit (Tx) signal, or a polarity-inverted versionof the Tx signal, during each step scan. The number and polarity of therows stimulated, may be controlled through control registers in the AFE400. The number of rows simultaneously stimulated during multi-Tx isdefined as a parameter N_(multi). N_(multi) may be a constant value fromstep-to-step within a given frame and also from frame-to-frame.

If N_(multi) rows are simultaneously stimulated during a step scan, itwill take at least N_(multi) step scans to resolve all the pixelcapacitances being stimulated. Each receiver has N_(multi) capacitancesbeing stimulated during a scan step. Hence there are N_(multi) unknowncapacitances, requiring at least N_(multi) measurements to resolve thesevalues. During each of these N_(multi) steps, the polarity control ofthe Tx rows will be modulated by a set of Hadamard sequences. Once thisset of N_(multi) (or more) step scans is complete, the next set ofN_(multi) rows can be stimulated in the same fashion, as N_(multi) willalmost always be less than the number of actual rows in the capacitivetouch panel 102.

In this way, the processing of the entire capacitive touch panel 102occurs in blocks, where N_(multi) rows of pixels are resolved during onebatch of step scans, and then the next N_(multi) rows of pixels areresolved in the next batch of step scans, until all the panel rows arefully resolved.

In most scenarios, the number of panel rows will not be an exactmultiple of N_(multi). In these situations, the number of rows scannedduring the final block of rows will be less than N_(multi). However,N_(multi) scan steps may be performed on these remaining rows, usingspecified non-square Hadamard matrices.

Analog Front End and Asymmetric Scan

FIGS. 5 and 6 show examples of asymmetric scan maps 500 and 600.

FIG. 7 shows a high-level architecture 700 of the analog front end 400(FIG. 4). The architecture 700 includes a transmit channel 702 providingsignals to columns of the capacitive touch panel 102 and a receivechannel 704 sensing signals from the capacitive touch panel 102. Thetransmit channel 702 includes a digital to analog converter 706,polarity control circuits 708 and buffers 710. The receive channel 704includes a pre-amplifier 712 and analog to digital converter 714.

All transmit channels may be driven by a shared transmit data signallabeled TxDAC in FIG. 7. Each physical transmit channel may also receivea common transmit digital to analog converter clock signal, labeledTxDacClk, to drive the transmit digital to analog converter 706. Theclock signal will come directly from a frequency locked loop blockwithin the TFE 132, and this clock signal will also be routed to thedigital portion of the TFE 132.

Each physical transmit channel may also have its own set ofchannel-specific TxCtrl bits that appropriately control variousparameters of the transmit channel, such as enable/disable, polaritycontrol, and gain/phase control. These TxCtrl bits are not updated atthe TxDacClk rate, but rather are updated between subsequent step scansduring the frame scan operation.

A control signal controls the transmit polarity of each of the 48transmit channels. As will be described in greater detail below, thepolarity of the transmit outputs may be modulated in an orthogonalsequence, with each transmit output having a fixed polarity during eachscan step during a frame scan.

All receive channels will receive a set of common clock signals. Theseclock signals are provided directly from a frequency locked loop blockwithin the TFE 132, and this clock signal is also routed to the digitalportion of the TFE 132. The clock signals routed to the RX channelsinclude the signal RxADCClk which drives the RxADC. A typical clockfrequency for this signal is 48 MHz.

Each physical receive channel will also have its own set ofchannel-specific receive control bits, labeled RxCtrl in FIG. 7, thatappropriately control various parameters of the receive channel, such asenable/disable and gain control. These receive control bits are updatedbetween subsequent step scans during the frame scan operation.

Additionally, there may be a shared set of control settings, labelledRxCtrlUniv in FIG. 7, that will control all receive channelssimultaneously. These registers are primarily composed of genericcontrol bits that will remain constant for a given implementation of thecontroller 104.

There are also one or more reset lines labeled RxReset that are commonto all reset channels. These reset lines may be asserted in a repeatablefashion prior to each scan step.

Waveform Generation

The waveform generation block (WGB) 404 in FIG. 4 generates the transmitwaveform for the TX channels 402. The WGB 404 generates a digital sinewave. Additionally, WGB 404 may generate other simple periodicwaveforms; such as square waves having edges with programmable rise andfall times.

The primary output of the WGB 404 is the data input to the transmitchannels 402 labelled TxDAC in FIG. 4. The WGB 404 receives as inputsignals a clock signal labelled TxDacClk and a signal labelled Start inFIG. 4. Upon receiving the Start signal from the scan controller 426,the WGB 404 begins producing digital waveforms for the duration of asingle step scan. At the conclusion of the step scan, the WGB 404 ceasesoperation and waits for the next start signal from the scan controller426.

The WGB 404 may have some amount of amplitude control, but the WGB 404will typically be operated at maximum output amplitude. Therefore, theperformance requirements listed below only need to be met at max outputamplitude. All signal outputs may be in two's complement format. The WGB404 may also provide arbitrary sine/cosine calculation capabilities forthe scan data path 408 and spectrum estimation preprocessor 432.

The following table lists typical performance for the WGB 404.

Specification Min Nom Max Comment Clock rate 8 MHz Will operate atTxDacClk rate. Output 0 Hz — 2 MHz frequency Frequency — 15 bits —Desired resolution of ctrl ~61 Hz. Can be resolution different. # ofoutput — 8 — bits Output 50% 100% 100% amplitude amplitude amplitudeamplitude Amplitude — 7 bits — Corresponds to 1% ctrl stepsize inamplitude resolution control. DC bias 0 0 0 All outputs should becontrol balanced around 0. Output THD −40 dBFs Sine wave mode only.Rise/fall 1 clock — 256 clock Square-wave mode time cycle @ cycles @only. Independent 8 MHz 8 MHz control of rise time vs. fall time NOTrequired.

Differential Scan Mode

Differential scan mode is an enhancement to normal scanning mode,whereby the frame scan operation is modified to exploit the correlationof the interference signal received across adjacent receive channels. Inthis mode, the normal frame scan methodology is performed; however thenumber of step scans used to assemble a single frame is doubled.Conceptually, each step scan in the scan sequence becomes two stepscans: the first is a single-ended or normal step scan with the defaultvalues for the AFE control registers, and the second is a differentialstep scan.

Given N_(RX) receive channels, the differential scan mode yields a totalof 2N_(RX) receiver measurements per aggregate scan step. (e.g. N_(RX)single-ended measurements and N_(RX) differential measurements.) These2N_(RX) measurements are recombined and collapsed into N_(RX) normalmeasurements in the Differential Combiner block 412, 418 shown in FIG.4.

In FIG. 4, the differential combiner blocks 412, 410 provide thecapability to operate in differential mode, where the receive channels406 alternate step scans between single-ended measurements anddifferential measurements. The purpose of the differential combinerblocks 412, 418 is to combine the N_(RX) single-ended measurements and(N_(RX)−1) differential measurements into a single set of N_(RX) finalresults for use in the heatmap assembly blocks 414, 420 that follow.

The differential combiner blocks 412, 418 are akin to a spatial filter.Let the vector, c, be an N_(rx)-by-1 vector of the capacitances toestimate. In differential mode, you have a vector, s, of single-endedmeasurements and a vector, d, of differential measurements. Hence, anestimate of c, called c_(est), is sought by optimally recombining s andd. Determining the optimal recombination requires substantialcomputation, but simulations have shown that the following recombinationscheme works to within roughly 0.5 dB of optimal performance over theexpected range of operating conditions:c _(est,n) =a ₁ ·s _(n−2) +a ₂ ·s _(n−) +a ₃ ·s _(n) +a ₂ ·s _(n+1) +a ₁·s _(n+2) +b ₁ ·+b ₂ ·d _(n) −b ₂ ·d _(n+1) −b ₁ ·d _(n+2)

where the subscript n indicates result from the n^(th) receiver channel,and 0≦n≦N_(RX)−1.

Furthermore, the coefficients are subject to the following constraints:0≦a₁,a₂,a₃≦1a ₃=1−2a ₁−2a ₂b₁=a₁b ₂ =a ₁ +a ₂

Given these constraints, it can be observed that the math operationlisted above can be collapsed into two multiplication operations:c _(est,n) =s _(n) +a ₁·(s _(n−2)−2s _(n) +s _(n+2) +d _(n−1) +d _(n) −d_(n+1) −d _(n+2))+a ₂·(s _(n−1)−2s _(n) +s _(n+1) +d _(n) −d _(n+1))

The equations above assume that the data exists for 2 receivers oneither side of the nth receiver. (e.g. 2≦n≦N_(RX)−3) Therefore, theequations above may be modified for the two outer edge receive channelson either side. The modifications are quite simple. First, replace anynon-existent s_(k) term with the nearest neighboring s_(j) term thatdoes exist. Second, replace any non-existent d_(k) term with 0. Puttingthese rules together and expressing the mathematics in matrix form, weget:

$c_{est} = {\begin{bmatrix}{a_{1} + a_{2} + a_{3}} & a_{2} & a_{1} & 0 & 0 & {- b_{2}} & {- b_{1}} & 0 & 0 \\{a_{1} + a_{2}} & a_{3} & a_{2} & a_{1} & 0 & b_{2} & {- b_{2}} & {- b_{1}} & 0 \\a_{1} & a_{2} & a_{3} & a_{2} & a_{1} & b_{1} & b_{2} & {- b_{2}} & {- b_{1}} \\\vdots & \vdots & \vdots & \vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\a_{1} & a_{2} & a_{3} & a_{2} & a_{1} & b_{1} & b_{2} & {- b_{2}} & {- b_{1}} \\0 & a_{1} & a_{2} & a_{3} & {a_{2} + a_{1}} & 0 & b_{1} & b_{2} & {- b_{2}} \\0 & 0 & a_{1} & a_{2} & {a_{3} + a_{2} + a_{1}} & 0 & 0 & b_{1} & b_{2}\end{bmatrix} \cdot {\quad\begin{bmatrix}s_{0} \\\vdots \\s_{N_{RX} - 1} \\d_{1} \\\vdots \\d_{N_{RX} - 1}\end{bmatrix}}}$

Lastly, while the optimal values of {a1, a2, a3, b1, b2} are dependentupon the precise noise and interference environment, it has been foundthat the following values for these parameters operate near optimalperformance for the expected range of operating environments:a₁=⅛a₂= 7/32a₃= 5/16b ₁=⅛·k _(ADC)b ₂= 11/32·k _(ADC)

The parameters b₁ and b₂ above are dependent upon another parameter,k_(ADC). The new parameter, k_(ADC), is dependent upon the value ofreceive channel analog to digital converter gain (Rx_AdcGain) usedduring the differential measurement step, as detailed in the tablebelow:

Rx_AdcGain<1:0> used during differential measurement step k_(ADC) 00 101 ¾ 10 ½ 11 ⅜

These a and b coefficients should be programmable by a control sourcesuch as firmware that is part of the controller 104, but the defaultvalues should be those listed above. The table below indicates thesuggested bit width for each coefficient:

Coefficient Bit width a₁ 5 a₂ 5 a₃ 5 b₁ 6 b₂ 8

The heatmap assembly blocks (HAB) 414, 420 take the step scan outputsfrom the scan data path 408 or differential combiners 412, 418, if used,and assemble the complete capacitive heatmap that is the major output ofthe frame scan operation. In order to do so, they may mathematicallycombine all of the step scan outputs in the appropriate manner to createestimates of the capacitance values of the individual capacitive pixelsin the capacitive touch panel 102.

As shown in FIG. 4, there are two separate and identical instantiationsof the HAB. A first HAB 414 is for the I-channel data and a second HAB420 is for the Q-channel data. Each HAB 414, 418 operates on the eitherthe I-channel or Q-channel data in order to create either an I-channelor a Q-channel capacitive heatmap.

In order to demonstrate the mathematics that may apply for heatmapassembly, an example 4×5 capacitive touch panel 800 is illustrated inFIG. 8. In this example, only the capacitive pixels in column 1 areanalyzed, but the same principle can be easily extended to each of thefive columns in the example capacitive touch panel 800. In particular,the output of receive column j is only affected by capacitance pixels incolumn j.

The example capacitive touch panel 800 includes a touch panel 802, atransmit digital to analog converter (TxDAC) 804, transmit buffers 806,808, 810, 812, and a receive analog to digital converter 814. Thetransmit buffers 806, 808, 810, 812 each have an associated multiplier816, 818, 820, 822, respectively. The multipliers 816, 818, 820, 822operate to multiply the applied signal from the TxDAC by either +1 or−1.

In the example of FIG. 8, a single TxDAC waveform is sent to all fourtransmit buffers 806, 808, 810, 812. However, each buffer multipliesthis waveform by either +1 or −1 before transmitting it onto the row ofthe touch panel 802. For a given step scan (indicated by the subscript“step_idx”), each value of H_(i,step) _(_) _(idx) is held constant. Butfor subsequent step scans in the scan sequence, these values may change.Therefore, at a given step index, the voltage received at m^(th) Rxchannel is:

$V_{{{step}\;\_\;{idx}},m} = {{V_{TX} \cdot {RxGain}_{m}}{\sum\limits_{n = 0}^{{NumRows} - 1}{H_{n,{{step}\;\_\;{idx}}} \cdot C_{n,m}}}}$

where V_(TX) is the amplitude of the transmit signal and RxGain_(m) isthe gain of the receive channel m. In order to simplify the analysis,these two parameters are assumed to be equal to 1 and ignored insubsequent calculations.

As can be seen by this equation above, V_(step) _(_) _(idx,m) is basedon NumRows (e.g. 4) unknown values, C_(n,m), with n=0 to 3 in thisexample. Therefore, if four independent step scans are performed withfour independent H sequences applied to the four transmit buffers 806,808, 810, 812, the relationship between V and C can be inverted in orderto estimate the C values from V. In matrix form, this can be written:

V_(m) = H ⋅ C_(m) $V_{m} = \begin{bmatrix}V_{0,m} \\V_{1,m} \\\vdots \\V_{{{NumSteps} - 1},m}\end{bmatrix}$ $H^{{NumSteps},{NumRows}} = \begin{bmatrix}H_{0,0} & \ldots & H_{0,{{NumRows} - 1}} \\\vdots & \ddots & \vdots \\H_{{{NumSteps} - 1},0} & \ldots & H_{{{NumSteps} - 1},{{NumRows} - 1}}\end{bmatrix}$ $C_{m} = \begin{bmatrix}C_{0,m} \\C_{1,m} \\\vdots \\C_{{{NumRows} - 1},m}\end{bmatrix}$

In this formulation, the column vector C_(m) represents the capacitanceof the capacitive pixels in the m^(th) column of the capacitive touchpanel. H is a NumSteps×NumRows matrix, where the n^(th) column of theH-matrix represents the multiplicative sequence applied to the n^(th)transmit row. The optional superscript of H indicates the dimensions ofthe H matrix. V_(m) is a column vector, where the n^(th) entry in thematrix is the n^(th) step scan output of m^(th) RX channel.

In the present application, H is a special form of matrix, called amodified Hadamard matrix. These matrices have the property that:H ^(T) ·H=NumSteps·I

where I is the NumRows×NumRows identity matrix, and H^(T) is thetranspose of H.

Given the formulation above, and the properties of the H-matrix, therelationship from C_(m) to V_(m) can be inverted in order to extract outthe values of the C_(m) vector from the V_(m) measurements. Using theterminology defined above:

$C_{m} = {\frac{1}{NumSteps}{H^{T} \cdot V_{m}}}$

In the example above, the panel had four rows and the value of NumSteps(equivalently N_(multi)) was also set to four. Therefore, all panel rowswere stimulated during every step scan. In general, the number of panelrows will be larger than the value of N_(multi). In that case, the panelstimulation is broken up into blocks. During each block of N_(multi)step scans, N_(multi) adjacent rows are stimulated with the Hadamardpolarity sequencing described above.

The heatmap assembly block 414, 420 works on each block of N_(multi)scans independently in order to create the complete heatmap output. Forinstance, if there were twelve panel rows and N_(multi) were set tofour, then the first four step scans would be used to stimulate andassemble the first four rows of the capacitive heatmap; the next fourstep scans would be for the fifth through eighth panel rows; and thelast four step scans would be for the ninth through twelfth rows.Therefore, for each block of N_(multi) rows, the heatmap assembly blockoperates in the exact same manner as defined above. However, the outputsof the HAB 414, 420 are mapped to the subsequent rows in the completecapacitive heatmap.

The heatmap assembly block 414, 420 is capable of assembling a32-column-wide heatmap, as there are a total of 32 receiver channelsimplemented in one embodiment. However, in many cases, the capacitivetouch panel used will not have 32 columns, and hence not all 32 receivechannels are used.

Mathematical Extensions for Asymmetric Panel Scanning

As described above, the controller 104 preferably has the capability toperform asymmetric panel scans, where the firmware supporting operationof the controller 104 has the capability to define the number of timeseach row is to be scanned. Given the formulation for asymmetric panelscanning outlined above, the changes to the heatmap assembly operationin order to support this feature are minimal.

As described above, the heatmap is assembled in blocks of N_(multi)rows. In asymmetric scanning, N_(multi) can vary on a block-by-blockbasis. Therefore, the old equation of:

$C_{m} = {\frac{1}{NumSteps}{H^{T} \cdot V_{m}}}$

is still valid. However, with asymmetric scanning, the dimensions of C,V, and H and the value of NumSteps change on a block-by-block basis.

The I/Q combiner 422 shown in 4 is used to combine the I- and Q-channelheatmaps into a single heatmap. The primary output of the I/Q combiner422 is a heatmap of the magnitude (e.g. Sqrt[I²+Q²]). This is theheatmap that is handed off to the touch back end 134.

The row/column normalizer 424 shown in FIG. 4 is used to calibrate outany row-dependent or column-dependent variation in the panel response.The row/column normalizer 424 has two static control input vectors,identified as RowFac and ColFac. RowFac is an Nrow-by-1 vector, whereeach entry is 1.4 unsigned number (e.g. LSB= 1/16. Range is 0 to 31/16).ColFac is an Ncol-by-1 vector, where each entry has the same dimensionsas RowFac.

If the input data to the Row/Column Normalizer block is labeled asHeatmapIn(m,n), where m is the row index and n is the column index, theoutput of the block should be:HeatmapOut(m,n)=HeatmapIn(m,n)·RowFac(m)·ColFac(n)

In one embodiment, the controller 104 has the capability to allow RowFacand ColFac to be defined either by OTP bits or by a firmwareconfiguration file. The OTP settings will be used if the manufacturingflow allows for per-module calibration, thus enabling the capability totune the controller 104 on a panel-by-panel basis. If RowFac and ColFaccan only be tuned on a per-platform basis, then the settings from afirmware configuration file will be used instead.

Spectrum Estimation

The spectrum estimation preprocessor 432 operates to determine thebackground levels of interference that couple into the receive channels406 so that the controller 104 may appropriately select transmitfrequencies that are relatively quiet or interference free.

The spectrum estimation preprocessor 432 will generally only be usedduring spectrum estimation mode, so it is not part of the standardpanel-scan methodology. Instead, the spectrum estimation preprocessor432 will be used when conditions indicate that SEM should be invoked. Atother times, the spectrum estimation preprocessor 432 can be powereddown.

Baseline Tracking and Removal Filter

A touch event should be reported when the measured capacitance of acapacitive pixel (or group of pixels) changes by a large enough amountin a short enough period of time. However, due to slow environmentalshifts in temperature, humidity or causes of drift, the absolutecapacitance of a pixel (or group of pixels) can change substantially ata much slower rate. In order to discriminate changes in pixelcapacitance due to a touch event from changes due to environmentaldrift, a baseline tracking filter can be implemented to track thechanges in the baseline (e.g. untouched or ambient value of thecapacitance), and simple subtraction of the baseline capacitance fromthe input capacitance will yield the change in capacitance due to thetouch event.

FIG. 9 illustrates a baseline tracking filter 900. The filter 900includes a low-pass filter (LPF) 902, a decimator 904 and a combiner906. The input signal to the filter 900 is provided to the combiner 906and the decimator 904. The output signal of the decimator is provided tothe input of the LPF 902. The output of the LPF 902 is combined with theinput signal at the combiner 906. The LPF 902 has an enable input forcontrolling operation of the filter 900.

The LPF 902 in the baseline tracking filter 900 is used to improve theestimate of the baseline capacitance value. One embodiment uses a simplefinite impulse response (FIR) moving average filter of length N (aka“comb filter”), such as:

${H_{N}(z)} = {{\frac{1}{N} \cdot \frac{1 - z^{- N}}{1 - z^{- 1}}} = {\frac{1}{N} \cdot {\sum\limits_{n = 0}^{N - 1}z^{- n}}}}$

Another embodiment a 1-tap infinite impulse response (IIR) filter, alsoreferred to as a modified moving average, with response:

${H_{k}(z)} = \frac{\frac{1}{k}}{1 - {\left( {1 - \frac{1}{k}} \right)z^{- 1}}}$

The FIR embodiment of the filter 902 may be used upon startup andrecalibration of the baseline value, as it can quickly acquire and trackthe baseline value. The IIR embodiment of the filter 902 should be usedonce the baseline value is acquired, as it can be a very computationallyefficient means to implement a low-pass filter, particularly if k ischosen to be a power of 2. By increasing the value of k, one can setchange the signal bandwidth of the filter to arbitrarily small valueswith minimal increase in computational complexity.

Filter 900 has two outputs, labeled “Out” and “Baseline” in FIG. 9. TheBaseline output is the estimate of the current baseline (aka ambient oruntouched) capacitance of the particular panel pixel(s) being scanned,and the Out output is the baseline-corrected value of that capacitancemeasurement. The Out value is what should be used in the subsequenttouch-detection logic.

The LPF 902 in FIG. 9 has an enable signal in order to shut down the LPF902 when a touch event is detected. This is provided so that thebaseline output is not corrupted by spurious data, most likely from atouch event. If the enable signal is low, the LPF 902 will hold itsprevious output without updating its output with the incoming data,effectively ignoring the incoming data. Once the enable signal is high,the LPF 902 will continue to update its output with the incoming data.Logic for generating the enable signal is detailed in the followingequation:Enable=(Out≦PosLPFThresh)&&(Out≧NegLPFThresh)

where PosLPFThresh and NegLPFThresh are configurable parameters.

In a mutual-capacitance scan mode, where a touch event causes areduction in the input data, the NegLPFThresh should be set tok_(T)*TouchThresh, where 0<k_(T)<1 and TouchThresh is thetouch-detection threshold defined below. These may both be programmableparameters. In a mutual-capacitance scan mode, there is no expectedphysical mechanism that would cause the input data to exhibit a positivetransient. Therefore, PosLPFThresh may be a programmable parameter usedto filter out spurious data, should an unexpected positive transientoccur.

Programmable Update Rate

The timescale of most baseline drift phenomena will be far slower thanthe frame rate of the touch panel scan. For instance, observed baselinedrift devices had timescales on the order of 1 hour or longer, whereasthe frame rate of a current device may be on the order of 200frames/second. Therefore, in order to reduce the computation forbaseline tracking, the controller circuit 104 shall have the capabilityto scale the update rate of the baseline tracking filter 900. The devicemay do this by using the decimator 904 to decimate the data fed to thefilter 900, so that the filter 900 only operates on every N_BTF_decimateframes of heatmap data, where N_BTF_decimate is a programmableparameter. Therefore, the Baseline signal in FIG. 9 will update at thisslower rate. However, the baseline corrected output signal (“Out” inFIG. 9) may be calculated for every frame.

Baseline tracking needs to exercise special care when spectrumestimation mode (SEM) is invoked. SEM may cause a configuration changein the analog front end which in turn will alter the gain in thetransfer function (e.g. from capacitance values to codes) of the touchfront end. This, in turn, may cause abrupt changes in the capacitiveheatmap to occur that could be accidentally interpreted as touch events.

A touch event is detected when the baseline-corrected output exhibits asignificant negative shift. The shift in this output may be larger thana programmable parameter, called TouchThresh. Furthermore, since thecontroller circuit 104 may scan a panel at upwards of 200 Hz and a humanfinger or metal stylus moves at a much slower timescale, a programmableamount of debounce, dubbed TouchDebounce, should also be included.Therefore, before a touch is recognized, the output of the baselinefilter may be more negative than TouchThresh for at least TouchDebounceframes. It is likely that TouchDebounce will be a small value, in orderthat the total touch response time is faster than 10 ms.

Heatmap Noise Estimation

The touch back end 134 requires an estimate of the noise level in thecapacitive touch panel 102 in order to properly threshold the touchblobs during the detection process. The noise level can be detected byobserving noise at the output of the baseline tracking filter as shownin FIG. 10. FIG. 10 shows a first variance estimator 1000 in conjunctionwith the baseline tracking filter 900 of FIG. 9. In FIG. 10, thebaseline tracking filter 900 has its Out output coupled to an input ofthe variance estimator 1000. The variance estimator 1000 includes adecimator 1002, a signal squarer 1004 and a low-pass filter 1006. Thevariance estimator 1000 in this embodiment is simply a mean-squareestimator, as the output of the baseline tracking filter 900 iszero-mean. Hence the mean-square is equal to the variance.

In order to lower the computational requirements for the varianceestimator 900, the data entering the variance estimator can be decimatedin the decimator 1002 by the factor, N_VAR_decimate. The low-pass filter1006 in the variance estimator 1000 may either be a comb-filter or amodified-moving-average filter. The length of the response of the filter1006 may be a programmable parameter, averaging data over as many as 100or more frames. In order to lower memory requirements, the MMA filtermay be preferred.

As with the baseline tracking filter 900, the LPF 1006 in the varianceestimator 1000 has an input for an enable signal. The enable signal islow when the pixel in question is being touched. Otherwise, the varianceestimate will be corrupted by the touch signal. When the enable signalis low, the LPF 1006 should retain state, effectively ignoring the datacoming into the variance estimator 1000.

The output of the variance estimator 1000 is the variance of one singlepixel in the capacitive touch panel 102. Therefore, this provides anindependent variance estimate of each pixel in the panel. To get anestimate of the variance across the panel 102, the controller circuit104 may average the per-pixel variances across the entire frame.

Alternately, if only a single per-frame variance estimate is needed, thecontroller circuit 104 can follow the approach shown in FIG. 10. FIG. 11shows a second variance estimator 1100 in conjunction with the baselinetracking filter 900 of FIG. 9. In FIG. 11, all the per-pixel baselinetracking filters are grouped as baseline tracking filters 900, on theleft in the figure. All the baseline-corrected outputs from the baselinetracking filters 900 are passed to the variance estimator 1100.

Like the variance estimator 1000 of FIG. 10, the variance estimator 1100includes a decimator 1102, a signal squarer 1104 and a low-pass filter1106. The variance estimator 1100 further includes a summer 1108. Thevariance estimator 1100 combines the outputs of the baseline trackingfilters 900 into a single value by summing the baseline-correctedoutputs across the entire frame in the summer 1108. This averaged valueis then passed to the same square-and-filter estimator that wasdescribed above, formed by the signal squarer 1104 and the low-passfilter 1106. Assuming that the noise is uncorrelated frompixel-to-pixel, the output of the variance estimator 1100 is equal tothe sum of all the pixel variances reported by the block diagram in FIG.10. In order to generate the average pixel variance across the panel,this result may be divided by the total number of pixels in thecapacitive touch panel 102. To generate an estimate of thestandard-deviation of the noise, the controller circuitry 104 may takethe square root of the variance.

Adaptive Reconfiguration

As described above, a high signal to noise ratio (SNR) of the signalreceived at the controller circuit 104 from the touch panel display isdesirable. In capacitive-touchscreen devices, many noise/interferencesources can couple onto the received channels 704 (FIG. 7). Interferersmay be due to noise from the LCD 112 (FIG. 1), noise from circuitcomponents such as thermal noise, quantization noise, flicker noise,etc.; noise from radio frequency (RF) circuitry; noise from the device'spower source such as battery 114 (FIG. 1); or noise from otherunidentified sources that couple onto the received signal. Frequently,these interferers are substantially larger than the desired signal, andhave many harmonic tones that are within the operating frequency of thetouch controller system. Hence, these interferers can significantlydegrade the SNR achieved by the touch controller system unless they areeither avoided or suppressed.

Interferers may vary in frequency, amplitude, phase, and quantity,depending on the device. Furthermore, these interferers are oftendynamic and can change rapidly, based on the operating conditions of thedevice. For instance, interference while using the device to view avideo may be substantially different than using the device to view awebpage. For example, FIG. 16 shows examples of the variability of theinterference spectrum. In one mode, the interference spectrum 1602 iscoupled onto received channels 704 (FIG. 7). In another mode, theinterference spectrum 1604 is coupled onto received channels 704 (FIG.7). As can be seen in FIG. 16, interference spectrum 1602 is quitedifferent from interference spectrum 1604. FIG. 17 shows the spectrum ofthe signal received by a received channel 704 (FIG. 7). The high levelof interference and noise in the interference spectrum 1702 contributesto a poor signal to noise ratio of the desired signal 1704. Because ofthe variability of interference and its source, reliable prediction andreduction of interference has heretofore been difficult to attain.

Various methods can be used to improve signal to noise ratio and/ormitigate poor signal to noise ratios. Such methods include increasingthe power level of the transmit signal, filtering the received signal,shielding the analog receiver from nearby spurious emissions, reducingcircuit noise, and/or performing additional scans. Additionally, thesignal to noise ratio of a signal received by an analog receiver can beimproved by selecting an optimal transmit frequency and/or by optimallyfiltering the received signal.

Given the variability of interferers, however, a fixed frequency or afixed filter may not provide an adequate signal to noise ratio withchanging conditions. It would be advantageous to adaptively reconfigurethe transmit frequency and/or adaptively reconfigure the filtering ofthe received channels. By adaptively reconfiguring the transmitfrequency and/or adaptively reconfiguring the received signal filtering,a higher signal to noise ratio can be achieved efficiently anddynamically for the variety of interferers that may couple to thereceived channels.

Referring to FIG. 12, it shows an adaptive reconfiguration process 1200.As contemplated in one implementation, the adaptive reconfigurationprocess begins at block 1202 where a triggering event is detected. Atriggering event can be used to initiate a process for adaptivelyreconfiguring the transmit frequency in the AFE and/or adaptivelyreconfiguring the filtering of the received signal. The triggering eventcan be timer-based or based on monitoring of the signal to noise ratio.For example, for a timer-based triggering, a processor, such as the scancontroller 426 (FIG. 4) could be programmed to detect a triggering eventonce every second. For a signal to noise ratio trigger, a processor suchas the scan controller 426 (FIG. 4) could be programmed to detect atriggering event when the SNR drops below a threshold level of 40 dB.

Once a triggering event has been detected, the adaptive reconfigurationprocess 1200 continues to block 1204 where the touch system switchesinto spectrum estimation mode. As described above, this mode is used tomeasure the interference and noise spectrum that couples into eachphysical receive channel 704 (FIG. 7). This spectrum estimation modeallows the touch system to measure and calculate the received signalacross a wide frequency band. In this mode, the scan controller 426(FIG. 4) instructs all TX channels 702 (FIG. 7) to stop transmitting andconfigures receive channels 704 (FIG. 7) for a wideband measurement.Without transmitting, the touch system is able to measure theinterferers and noise across the entire relevant available frequencyband. For example, in some cases, the relevant available frequency bandof the physical receive channel 704 (FIG. 7) may be between 0 MHz and 1MHz, but other frequency bands may be used, depending on the specificparameters of physical receive channel 704 circuitry. The scancontroller 426 (FIG. 4) can be used to set the touch system to spectrumestimation mode.

While the touch system is operating in spectrum estimation mode, thespectrum estimation preprocessor 432 (FIG. 4) determines theauto-correlation of the received signal to measure its spectralcomponents. Because this received signal is captured while operating inspectrum estimation mode, the spectral components of the received signalwill include only interferers and other noise. Thus, from the spectrumestimation mode measured signal, the spectrum estimation preprocessor432 can calculate the auto-correlation function of the interferers andother noise.

Using the auto-correlation of the interferers and other noise determinedin block 1204 of the adaptive reconfiguration process 1200, the processcontinues to block 1206 where a processor, such as processor 122(FIG. 1) or a processor in the TBE 134 (FIG. 1) uses theauto-correlation function of the interferers and noise to determine adesired transmit frequency to be used for the transmit channels 402(FIG. 4) of the analog front end 400 (FIG. 4). After the desiredtransmit frequency is determined, the adaptive configuration process1200 continues to block 1208, where the determined transmit frequency isapplied to the transmit channels 402 (FIG. 4) of the AFE 400 (FIG. 4).

In order to determine an optimal transmit frequency, the spectrumestimation preprocessor 432 (FIG. 4) can calculate the mean square error(MSE) of the filter transfer function associated with each availabletransmit frequency. An optimal transmit frequency (f_(opt)), then, isthe transmit frequency that corresponds to the minimum MSE. For example,when available transmit frequencies range from 100 kHz to 800 kHz insteps of 10 kHz, there are seventy-one frequencies for which an MSE ofthe filter transfer function can be calculated. Those of ordinary skillin the art will recognize that other frequency ranges and frequencysteps can also be used. The transmit frequency for which the MSEcalculation results in the smallest MSE is an optimal transmitfrequency. For example, assuming the auto-correlation of the interfereris r_(v)(n), and assuming the interferer is filtered using a filter ofimpulse response h₂(n), the output auto-correlation will ber_(y)(n)=r_(v)(n)*h₂(n)*h₂(−n), where ‘*’ denotes convolution and theoutput power is given by r_(y)(0). The filter of impulse response h₂(n)is assumed to be centered at a given frequency ω₀. In oneimplementation, h₂ could be an FIR filter of length L₂ of the formh₂(n)=sin(ω₀n+θ), n=0, . . . , L₂−1, for some θ. The spectrum estimationprocessor 432 can tune h₂ to different frequencies and compute r_(y)(0)for each frequency. In such a manner, the spectrum estimation process432 can determine the frequency that yields the lowest noise power, andtherefore minimizes the MSE.

By way of example, presume the received signal is r(n)=A sin(ω₀n+θ)+v(n)where n=0, . . . , L−1 and L is the length of the observation window; Ais the unknown amplitude we wish to determine; ω₀ is the transmitfrequency used by the TX 402; θ is the phase of the received signal; andv(n) is the interference plus noise (assumed to be random). In vectornotation, the received signal can be written r=As_(θ)+v. Assuming theinterferer is zero-mean and represented by the covariance matrix R_(v),the best linear unbiased estimator of A given s_(θ) is given by thefilter

$h = \frac{R_{v}^{- 1}s_{\theta}}{s_{\theta}^{*}R_{v}^{- 1}s_{\theta}}$and the resulting minimum MSE can be written MSE=h*R_(v)h=1/(s*_(θ)R_(v)⁻¹s_(θ)). An optimal transmit frequency minimizes the MSE, orequivalently maximizes s*_(θ)R_(v) ⁻¹s_(θ). Once an optimal transmitfrequency is found, an optimal filter can be calculated to rejectinterferers and reduce noise.

To summarize an implementation of blocks 1202, 1204, 1206, and 1208 ofthe adaptive reconfiguration process 1200 (FIG. 12) by referring to FIG.4, a triggering event occurs and the scan controller 426 is notified bya processor such as processor 122 (FIG. 1) that the frequency used bythe transmit channels 402 and/or to the filtering in the scan data path408 should be updated. To determine the transmit frequency, the scancontroller 426 sets the received channels 406 to spectrum estimationmode, and operates as described above. The spectrum estimationpreprocessor 432 determines the auto-correlation waveform data andprovides this data to a processor such as processor 122 (FIG. 1). Theprocessor 122 (FIG. 1) calculates the MSE for each available frequency.Then, the frequency that corresponds to the minimum MSE is determined,which is an optimal frequency (f_(opt)) for use by the transmit channels402. This optimal frequency is reported to the scan controller 426 andthe transmit frequency parameter of the waveform generation block (WGB)404 is configured to use this optimal frequency (f_(opt)). In addition,the receive frequency of the AFE is configured to use this optimalfrequency.

The adaptive reconfiguration process 1200 continues to block 1208 wherea processor such as processor 122 (FIG. 1) determines the adaptivefilter transfer function for use in the scan data path 408 (FIG. 4). Aprocessor such as processor 122 (FIG. 1) calculates an optimal filtertransfer function and corresponding filter coefficients based on thecorrelation data provided from the spectrum estimation preprocessor 423(FIG. 4) that was measured and calculated in block 1204. These filtercoefficients will be used by the interferer filter contained in scandata path 408 (FIG. 4). After the desired filer coefficients aredetermined, the adaptive configuration process 1200 continues to block1212, where the determined transfer function is applied to theinterferer filter contained in the scan data path 408 (FIG. 4).

Determining the MSE of the filter transfer function for each frequencymay require significant processing. While many methods may be used toreduce the amount of processing required to calculate the MSE of thefilter transfer function, such as reducing the available frequency rangeor increasing the step frequency, one method is to form a filtertransfer function by cascading a fixed, but tunable, filter with anadaptive filter. In this manner, the amount of processing is reducedbecause the fixed filter will have a known filter transfer functionwhich simplifies the calculations for the adaptive filter transferfunction.

Referring to FIG. 13, an example of a scan data path 1300 is shown whichreceives data from the AFE 400 (FIG. 4) and transmits data to the I/Qchannels of HAB 414, 420 via in-phase (I) and quadrature (Q) outputs.Those of ordinary skill in the art will recognize that a single-endedscan data path may also be used. The scan data path 1300 shows thatfiltering occurs in interference filter 1304 and integration filters1306A and 1306B. In one implementation, the filter transfer function hfor the scan data path is comprised of two cascaded filters, h₁ and h₂.Interference filter 1304 (h₁) is tuned to reduce variable interfererswhile integration filters 1306A-B (h₂) are tuned for overall noisereduction.

The filter transfer function h can be written h=H₂h₁, where the adaptivefilter is h₁ and H₂ is a fixed convolution matrix based on filter h₂.Thus,

${h_{1} = \frac{\left( {H_{2}^{*}R_{v}H_{2}} \right)^{- 1}H_{2}^{*}s}{s^{*}{H_{2}\left( {H_{2}^{*}R_{v}H_{2}} \right)}^{- 1}H_{2}^{*}s}},{and}$${MSE} = {\frac{1}{s^{*}{H_{2}\left( {H_{2}^{*}R_{v}H_{2}} \right)}^{- 1}H_{2}^{*}s}.}$If differential in-phase (I) and quadrature (Q) demodulation is used,then h₁=H_(2I)h₁ and h_(Q)=H_(2Q)h_(1.)

To compute h₁, we then use h₁=α(H*₂R_(v)H₂)⁻¹H*₂s, where α is anormalization constant and the matrix H*₂R_(v)H₂ is a Toeplitz matrixand s is a sinusoid of the transmit frequency f_(stim). Thus, h₁ can beefficiently computed using a Durbin algorithm.

FIGS. 14A-C show various implementations of cascaded filter transferfunctions h₁ and h₂ in a single-ended scan data path. Those of ordinaryskill in the art will recognize that a differential in-phase (I) andquadrature (Q) scan data path may be used. FIG. 14A shows a simple scandata path with a decimation block 1402, interference filter 1404 (h₁),and integration filter 1406 (h₂). The interference filter 1404 (h₁) canbe, for example, a multi-tap digital filter having variable filtercoefficients that can be tuned to reduce various types of interference.FIG. 14B shows a similar scan data path, but integration filter 1406(h₂) is comprised of an integration filter 1406A (h₂₋₁) cascaded with anintegration filter 1406B (h₂₋₂). FIG. 14C shows that the filters can becascaded in various orders.

FIG. 15 shows an implementation of the scan data path 432 as itinteracts with the spectrum estimation preprocessor 408 and theprocessor 102. The scan data path 432 contains decimation filter 1502,which can be implemented by a multi-tap symmetric filter for removingout of band noise and reducing the sampling rate. Bandpass filtering isperformed in two stages by an integration filter 1504 anddifferentiation filter 1508. In between the two-staged bandpass filteris interference filter 1506, which has a configurable filter transferfunction (h₁). After filtering is performed in scan data path 1510, thedifferential in-phase (I) and quadrature (Q) signals are fed to the I/Qchannels of the HAB 414, 420 (FIG. 4).

In order to configure the filter transfer function (h₁) for theadjustable interference filter 1506, the spectrum estimationpreprocessor 408 is used. The spectrum estimation preprocessor 408receives the output of the decimation filter 1502 and determines theauto-correlation of the received signal. The channel averaging block1542 selects either the received signal interference/noise of anindividual physical receive channel or averages the received signalinterference/noise across all physical receive channels. Next, thedetector block 1544 uses a threshold value to detect the presence of aninterferer that may require filtering by the adjustable interferencefilter 1506. The bandpass filter block (BPF) 1546 applies the estimatedbandpass filter transfer function that results from cascading bandpassintegration filter 1504 with bandpass differentiation filter 1508 in thescan data path. BFP block 1546 can be bypassed to compute the widebandauto-correlation. The auto-correlation of the interferer is calculatedin the compute correlation block 1548 of the spectrum estimationpreprocessor 408. The processor 102 receives this interferer spectruminformation from the spectrum estimation bock 408, which can be via abuffered memory 1514. The processor 102 calculates an optimal filtertransfer function as described above, and then calculates an optimalfilter transfer function for use by the interference filters 1506, whichcan be via a buffered memory 1514.

Referring to FIG. 18, it shows a received signal spectrum 1800, whichincludes the desired signal 1704, the interference spectrum 1702 and thefrequency response of the adaptive filter 1802. After applying thefilter transfer function to the received signal spectrum 1800, thefiltered received signal spectrum 1810 results. The interferers andnoise from the interference spectrum 1702 are now reduced, and thesignal to noise ratio of the desired signal 1704 is improved.

The methods, devices, and logic described above seek to efficiently andreliably provide a high signal to noise ratio for measuring thecapacitance of the touch panel. By adaptively determining the frequencyof the signal transmitted to the touch panel and then filtering thereceived signal using an adaptive filter, the touch device becomesrobust to dynamic interference variations, and improves the touchperformance of the touch panel device.

The methods, devices, and logic described above may be implemented inmany different ways in many different combinations of hardware,software, or both hardware and software. For example, all or parts ofthe system may include circuitry in a controller, a microprocessor, oran application specific integrated circuit (ASIC), or may be implementedwith discrete logic or components, or a combination of other types ofanalog or digital circuitry, combined on a single integrated circuit ordistributed among multiple integrated circuits. All or part of the logicdescribed above may be implemented as instructions for execution by aprocessor, controller, or other processing device and may be stored in atangible or non-transitory machine-readable or computer-readable mediumsuch as flash memory, random access memory (RAM) or read only memory(ROM), erasable programmable read only memory (EPROM) or othermachine-readable medium such as a compact disc read only memory (CDROM),or magnetic or optical disk. Thus, a product, such as a computer programproduct, may include a storage medium and computer readable instructionsstored on the medium, which when executed in an endpoint, computersystem, or other device, cause the device to perform operationsaccording to any of the description above.

The processing capability of the system may be distributed amongmultiple system components, such as among multiple processors andmemories, optionally including multiple distributed processing systems.Parameters, databases, and other data structures may be separatelystored and managed, may be incorporated into a single memory ordatabase, may be logically and physically organized in many differentways, and may implemented in many ways, including data structures suchas linked lists, hash tables, or implicit storage mechanisms. Programsmay be parts (e.g., subroutines) of a single program, separate programs,distributed across several memories and processors, or implemented inmany different ways, such as in a library, such as a shared library(e.g., a dynamic link library (DLL)). The DLL, for example, may storecode that performs any of the system processing described above. Whilevarious embodiments of the invention have been described, it will beapparent to those of ordinary skill in the art that many moreembodiments and implementations are possible within the scope of theinvention. Accordingly, the invention is not to be restricted except inlight of the attached claims and their equivalents.

What claimed is:
 1. A method for reconfiguring a capacitive touchcontroller, the method comprising: detecting a triggering event forreconfiguring the capacitive touch controller; measuring a receivedsignal from a capacitive touch panel; determining an auto-correlation ofthe received signal; determining a filter transfer function forrejecting interference from a subsequently received signal, where thefilter transfer function is based on the auto-correlation of thereceived signal; determining a transmit frequency for stimulating thecapacitive touch panel, where the transmit frequency is based on theauto-correlation of the received signal, including determining anoptimal transmit frequency from a range of available frequencies, whereeach available frequency has a mean square error (MSE), where the MSE isdetermined by the inner product of the auto-correlation of the receivedsignal and auto-correlation of the filter transfer function, and wherethe optimal transmit frequency is the available frequency having theminimum MSE; stimulating the capacitive touch panel using the transmitfrequency by applying to the capacitive touch panel a time varyingsignal having the transmit frequency, and subsequently receiving asignal from the capacitive touch panel, the subsequently received signalbeing indicative of a response of the capacitive touch panel to the timevarying signal; and filtering a subsequently received signal using thefilter transfer function.
 2. The method of claim 1, where the triggeringevent occurs when signal to noise ratio (SNR) of the received signal isbelow a threshold SNR value.
 3. The method of claim 1, where thetriggering event occurs when a period of time has elapsed.
 4. The methodof claim1, where determining the filter transfer function comprisesdetermining a bandpass filter transfer function in series with a finiteimpulse response filter transfer function, wherein the filter transferfunction is calculated to improve signal to noise ratio (SNR) of thesubsequently received signal.
 5. The method of claim 4, wheredetermining the filter transfer function for the finite impulse responsefilter comprises determining filter coefficients for a multi-tap digitalfilter.
 6. The method of claim 1, wherein determining the transmitfrequency for stimulating the capacitive touch panel comprisesdetermining the best linear unbiased estimator from the auto-correlationof the received signal.
 7. A capacitive touch controller comprising: adetector configured to detect a triggering event for reconfiguring thecapacitive touch controller; a signal processor configured to measure areceived signal from a capacitive touch panel of the capacitive touchcontroller and determine auto-correlation of the received signal; afilter processor configured to determine a filter transfer function forrejecting interference from a subsequently received signal, where thefilter transfer function is based on the auto-correlation of thereceived signal; a frequency processor configured to determine atransmit frequency for stimulating the capacitive touch panel, where thetransmit frequency is an optimal transmit frequency selected from arange of available frequencies, where each available frequency has amean square error (MSE), where the MSE is determined by the innerproduct of the auto-correlation of the received signal and theauto-correlation of the filter transfer function, and where the optimaltransmit frequency is the available frequency having the minimum MSE; atransmitter configured to stimulate the capacitive touch panel using thetransmit frequency; and a filter configured to apply the filter transferfunction to a subsequently received signal.
 8. The controller of claim7, where the triggering event occurs when signal to noise ratio (SNR) ofthe received signal is below a threshold SNR value.
 9. The controller ofclaim 7, where the triggering event occurs when a period of time haselapsed.
 10. The controller of claim 7, where the filter transferfunction comprises a bandpass filter transfer function in series with afinite impulse response filter transfer function, wherein the filtertransfer function is calculated to improve signal to noise ratio (SNR)of the subsequently received signal.
 11. The controller of claim 10,where the filter transfer function for the finite impulse responsefilter comprises a multi-tap digital filter.
 12. The controller ofclaim7, wherein the filter processor comprises a circuit configured todetermine the filter transfer by determining the best linear unbiasedestimator from the auto-correlation of the received signal.
 13. Aportable data processing device comprising: a video display; acapacitive touch panel; a control circuit operative to provide signalsto the video display to produce images on the video display andoperative to detect touch interactions with the capacitive touch panel,the control circuit including a capacitive touch controller comprising:a detector configured to detect a triggering event for reconfiguring thecapacitive touch controller; a signal processor configured to measure areceived signal from the capacitive touch panel of the portable dataprocessing device and determine auto-correlation of the received signal;a filter processor configured to determine a filter transfer functionfor rejecting interference from a subsequently received signal, wherethe filter transfer function is based on the auto-correlation of thereceived signal; a frequency processor configured to determine atransmit frequency for stimulating the capacitive touch panel with astimulation signal applied to the capacitive touch panel, where thetransmit frequency is an optimal transmit frequency selected from arange of available frequencies, where each available frequency has amean square error (MSE), where the MSE is determined by the innerproduct of the auto-correlation of the received signal andauto-correlation of the filter transfer function, and where the optimaltransmit frequency is the available frequency having the minimum MSE; atransmitter configured to stimulate the capacitive touch panel using thetransmit frequency; and a filter configured to apply the filter transferfunction to a subsequently received signal.
 14. The portable dataprocessing device of claim 13, where the triggering event occurs whensignal to noise ratio (SNR) of the received signal is below a thresholdSNR value or when a period of time has elapsed.
 15. The portable dataprocessing device of claim 13, where the filter transfer functioncomprises a bandpass filter function in series with a finite impulseresponse filter function, wherein the filter transfer function iscalculated to improve signal to noise ratio (SNR) of the subsequentlyreceived signal by filtering noise coupled to the received signal by thevideo display, the capacitive touch panel, and/or the touch controller.16. The portable data processing device of claim 15, where the filtertransfer function for the finite impulse response filter comprises amulti-tap digital filter.
 17. The portable data processing device ofclaim 13, wherein the signal processor comprises a circuit configured todetermine the auto-correlation of the received signal by determining thebest linear unbiased estimator from the auto-correlation of the receivedsignal.